High-speed wire harness assembly method and system based on intelligent algorithm detection

Abstract

This invention relates to the field of machine vision technology, specifically a high-speed wire harness assembly method and system based on intelligent algorithm detection. The method includes: identifying multiple original conductors based on wire harness specifications; acquiring end-face images of the original conductors to obtain conductor images; determining the insulation layer thickness based on the conductor images; stripping the original conductors using the insulation layer thickness and a laser wire stripper to obtain qualified stripped conductors; performing core detection on the qualified stripped conductors to obtain core detection reports; identifying multiple qualified conductors based on multiple core detection reports; crimping terminals using the multiple qualified conductors to obtain multiple crimped conductors; verifying the crimping quality of each crimped conductor to obtain multiple qualified crimped conductors; and bundling the multiple qualified crimped conductors to obtain multiple bundled wire harnesses. This invention can solve the problem of low finished product yield caused by insufficient stripping accuracy and poor crimping quality during high-speed wire harness assembly.

Description

Technical Field

[0001] This invention relates to the field of machine vision technology, and in particular to a high-speed wire harness assembly method and system based on intelligent algorithm detection. Background Technology

[0002] With the rapid development of machine vision technology, high-speed wire harness assembly faces new challenges. To achieve high-efficiency high-speed wire harness assembly, image recognition can be used to intelligently detect wires and control laser wire stripping to ensure stripping accuracy. Then, the quality of the crimped wires is checked, and finally, the qualified wire harnesses are automatically bundled and assembled. This effectively solves the problem of low finished product qualification rate caused by insufficient stripping accuracy and poor crimping quality in the high-speed wire harness assembly process.

[0003] Currently, high-speed wire harness assembly mainly relies on manual labor, supplemented by semi-automated equipment in some stages. Although traditional semi-automatic equipment can basically achieve the assembly of high-speed wire harnesses, in daily production, insufficient operational precision leads to damage to the wire cores, causing transmission impairment and rendering the high-speed wire harness unusable. Therefore, optimizing the high-speed wire harness assembly method is of great significance for improving production efficiency and quality. Summary of the Invention

[0004] This invention provides a high-speed wire harness assembly method based on intelligent algorithm detection and a computer-readable storage medium. Its main purpose is to solve the problem of low finished product qualification rate caused by insufficient wire stripping accuracy and poor crimping quality during the assembly of high-speed wire harnesses.

[0005] To achieve the above objectives, the present invention provides a high-speed wire harness assembly method based on intelligent algorithm detection, comprising: Receive the wire harness assembly signal and determine the wire harness specifications based on the wire harness assembly signal; Multiple original conductors were identified based on the wire harness specifications; Perform the following operation on each of the multiple original conductors: The end face image of the original conductor is acquired to obtain the conductor image; The insulation layer thickness was determined based on the wire image; The original conductor is stripped using a laser wire stripper with pre-confirmed insulation layer thickness and a pre-determined insulation layer thickness to obtain a qualified stripped conductor. The core of the qualified stripped conductor is tested to obtain a core test report, which indicates whether it is qualified or unqualified. By summarizing the aforementioned core inspection reports, multiple core inspection reports are obtained; Multiple qualified conductors were confirmed based on multiple conductor test reports; Multiple qualified wires are used to crimp the terminals to obtain multiple crimped wires; The crimping quality of multiple crimped wires was checked, and multiple qualified crimped wires were obtained. Multiple qualified crimped wires were bundled together to obtain multiple bundled wire bundles.

[0006] Optionally, the step of stripping the original conductor using a laser wire stripper with pre-confirmed insulation layer thickness to obtain a qualified stripped conductor includes: Using a laser wire stripper, the insulation layer thickness, and a preset stripping length, the original wire is laser stripped to obtain a stripped wire. Obtain the image of the stripped wire; A pre-built edge detection algorithm is used to detect the stripping length of a stripped wire image, and the detected length is obtained. The stripping deviation is calculated using the detection length and the stripping length. The wire stripping deviation is compared with a preset deviation threshold. If the wire stripping deviation is less than the deviation threshold, the wire stripped is considered a qualified wire stripped. If the stripping deviation is greater than or equal to the deviation threshold, the stripped wire is treated as the original wire, and the process returns to the step of acquiring the end face image of the original wire until the stripping deviation is less than the deviation threshold, at which point the stripped wire is considered a qualified stripped wire.

[0007] Optionally, the step of performing core testing on qualified stripped conductors to obtain a core testing report includes: Surface quality is tested on qualified stripped conductors to obtain a surface quality score. If the surface quality score is less than the preset surface quality score threshold, a core inspection report is obtained, and the core inspection report is unqualified. If the surface quality score is greater than or equal to the surface quality score threshold, the end face image of the qualified stripped wire is acquired using a pre-confirmed ring low-angle light source. Extract multiple closed edge points using end-face images; The optimal circle is obtained by performing least-squares circle fitting using multiple closed edge points. Distance deviations are calculated using multiple closed edge points and the optimal circle, resulting in multiple distance deviations, each corresponding to a closed edge point. Obtain the maximum distance deviation among multiple distance deviations, and use the maximum distance deviation to calculate roundness; Obtain the core silhouette of a qualified stripped conductor; Thresholding is applied to the wire core silhouette to obtain a binary image; Use binary images to obtain the outer contour image and inner hole image of the wire core; The area of ​​the outer contour of the wire core is obtained from the outer contour image of the wire core, and the area of ​​the inner hole is obtained from the inner hole image. The proportion of the wire core is calculated using the outer contour area of ​​the wire core and the preset nominal area; The proportion of the inner hole is calculated using the outer contour area of ​​the wire core and the area of ​​the inner hole. The roundness is compared with the preset roundness threshold, the core proportion is compared with the preset core proportion threshold, and the inner hole proportion is compared with the preset inner hole proportion threshold. If the roundness is greater than or equal to the roundness threshold, the core proportion is greater than or equal to the core proportion threshold, and the inner hole proportion is less than the inner hole proportion threshold, then a core inspection report is obtained, and the core inspection report is qualified. If the roundness is less than the roundness threshold, the core proportion is less than the core proportion threshold, or the internal hole proportion is greater than or equal to the internal hole proportion threshold, then a core inspection report is obtained, and the core inspection report is unqualified.

[0008] Optionally, the surface quality inspection of the qualified stripped conductor to obtain a surface quality score includes: Surface images of qualified stripped conductors are acquired to obtain conductor surface images; The conductor surface image is filtered and denoised to obtain a denoised conductor surface image; The noise-reduced conductor surface image is converted to grayscale to obtain a grayscale conductor surface image; Edge contours are extracted from grayscale conductor surface images to obtain the area of ​​scratch contours; Calculate the local binary mode variance map using grayscale conductor surface images; The local binary pattern variance map is binarized and segmented to obtain the potential ablation region; Obtain the scorch area of ​​the potential scorch region; The surface quality score is calculated using the scratch contour area and the burned area. The formula for calculating the surface quality score is as follows:

[0009] in, Indicates the surface quality score. This represents the preset scratch weight coefficient. Indicates the area of ​​the scratch outline. This represents the preset scorching weight coefficient. Indicates the area burned.

[0010] Optionally, the method of crimping terminals using multiple qualified wires to obtain multiple crimped wires includes: For each of the multiple qualified conductors, perform the following operation: The qualified wires are transported to the pre-confirmed crimping station, and the qualified wires are mechanically positioned using the pre-confirmed guide groove to obtain the ready-to-use wires. Obtain wire harness terminals; The wire harness terminals are transported to the crimping station, where a pre-confirmed industrial camera is used to capture images of the wire harness terminals, thus obtaining terminal images. The overall pose deviation is calculated using the terminal image and the pre-constructed reference template image; The overall pose deviation is compared with a preset pose deviation threshold. If the overall pose deviation is less than the pose deviation threshold, the wire harness terminal is used as a standby terminal. If the overall pose deviation is greater than or equal to the pose deviation threshold, a pose adjustment command is generated. The pose adjustment command and the pre-confirmed calibration nozzle are used to calibrate the wire harness terminal to obtain a calibrated terminal. The calibrated terminal is used as the wire harness terminal, and the process returns to the step of using the pre-confirmed industrial camera to acquire images of the wire harness terminal until the overall pose deviation is less than the pose deviation threshold. The wire harness terminal is then used as a standby terminal. The wire to be used and the terminal to be used are crimped together to obtain a crimped wire; By combining the crimped wires, multiple crimped wires are obtained.

[0011] Optionally, the step of calculating the overall pose deviation using the terminal image and the pre-constructed reference template image includes: The terminal image is preprocessed to obtain a preprocessed terminal image; Template matching is performed using the preprocessed terminal image and the reference template image to obtain the matched terminal image; Obtain multiple reference feature points from the matching terminal image; The coordinates of multiple reference feature points are obtained using multiple reference feature points and a pre-constructed rectangular coordinate system; Multiple reference feature points are obtained based on the coordinates of multiple reference feature points, and the coordinates of multiple reference feature points are obtained. Among them, the reference feature points and the reference feature points correspond one-to-one. A rigid transformation matrix is ​​constructed using the coordinates of multiple reference feature points and multiple reference feature points. The rigid transformation matrix includes a translation vector and a rotation matrix. The positional deviation is calculated using the translation vector. The attitude deviation angle is calculated using the rotation matrix. The overall pose deviation is calculated using the position deviation amount and the attitude deviation angle.

[0012] Optionally, constructing a rigid transformation matrix using multiple reference feature point coordinates and multiple reference feature point coordinates includes: Calculate the coordinates of the reference centroid using the coordinates of multiple reference feature points; Calculate the reference centroid coordinates using the coordinates of multiple reference feature points; Using the reference centroid, the coordinates of each of the multiple reference feature points are centered to obtain multiple centered reference feature point coordinates, where the centered reference feature point coordinates correspond one-to-one with the reference feature point coordinates. Multiple centered reference feature point coordinates are obtained using the reference centroid coordinates and multiple reference feature point coordinates, wherein the coordinates of the centered reference feature point correspond one-to-one with the coordinates of the reference feature point. A covariance matrix is ​​constructed using the coordinates of multiple centralized benchmark feature points and multiple centralized reference feature points; Singular value decomposition is performed on the covariance matrix to obtain the left singular vector matrix and the right singular vector matrix; Calculate the rotation matrix using the left and right singular vector matrices; Calculate the translation vector using the reference centroid coordinates, the datum centroid coordinates, and the rotation matrix; A rigid transformation matrix is ​​constructed using the rotation matrix and translation vector.

[0013] Optionally, the step of verifying the crimping quality of multiple crimped wires to obtain multiple qualified crimped wires includes: Perform the following operation on each of the multiple crimped wires: Obtain an image of the terminal area of ​​the crimped wire; The terminal area image is smoothed and filtered to obtain a noise-reduced image; Based on the pre-confirmed qualified terminal image, the noise-reduced image is used to locate the terminal to obtain the located image; Global illumination compensation is performed on the positioned image using the qualified terminal image to obtain the compensated image; Image difference processing is performed using the compensated image and the qualified terminal image to obtain the difference image; The difference image is binarized to obtain a binary difference image; The defect area is calculated using a binary difference image. The defect area is then compared with a preset defect area threshold. If the defect area is less than the defect area threshold, the crimped wire is considered a qualified crimped wire. By summarizing the qualified crimped wires, multiple qualified crimped wires are obtained.

[0014] Optionally, the step of performing global illumination compensation on the positioned image using the qualified terminal image to obtain the compensated image includes: The system acquires multiple actual grayscale values ​​of the image after positioning and multiple template grayscale values ​​of the qualified terminal image, wherein the actual grayscale values ​​correspond one-to-one with the template grayscale values. Calculate the mean and standard deviation of the actual grayscale using multiple actual grayscale values; Calculate the mean gray level and standard deviation of the template gray level using multiple template gray level values; For each of the multiple actual grayscale values, perform the following operation: The compensated gray value is calculated using the actual gray value, the actual gray mean, the actual gray standard deviation, the template gray mean, and the template gray standard deviation. The formula for calculating the compensated gray value is shown below:

[0015] in, Indicates the compensation standard deviation, Indicates the standard deviation of template grayscale. Indicates the actual grayscale standard deviation. This represents the actual grayscale value. This represents the average grayscale value of the template. This represents the actual average gray level. By summing the aforementioned compensation grayscale values, multiple compensation grayscale values ​​are obtained; The multiple compensated grayscale values ​​are mapped to the localized image to obtain the compensated image.

[0016] To achieve the above objectives, the present invention also provides a high-speed wire harness assembly system based on intelligent algorithm detection, comprising: The original wire stripping module is used to receive the wire harness assembly signal and determine the wire harness specifications based on the wire harness assembly signal; Multiple original conductors were identified based on the wire harness specifications; Perform the following operation on each of the multiple original conductors: The end face image of the original conductor is acquired to obtain the conductor image; The insulation layer thickness was determined based on the wire image; The original conductor is stripped using a laser wire stripper with pre-confirmed insulation layer thickness and a pre-determined insulation layer thickness to obtain a qualified stripped conductor. The core quality inspection module is used to inspect the cores of qualified stripped conductors and obtain a core inspection report, which indicates whether the conductor is qualified or unqualified. By summarizing the aforementioned core inspection reports, multiple core inspection reports are obtained; The wire terminal crimping module is used to identify multiple qualified wires based on multiple wire core test reports; Multiple qualified wires are used to crimp the terminals to obtain multiple crimped wires; The crimping quality of multiple crimped wires was checked, and multiple qualified crimped wires were obtained. The qualified wire bundling module is used to bundle multiple qualified crimped wires together to obtain multiple bundled wire bundles.

[0017] To address the above problems, the present invention also provides an electronic device, the electronic device comprising: Memory, storing at least one instruction; and The processor executes the instructions stored in the memory to implement the high-speed wire harness assembly method based on intelligent algorithm detection described above.

[0018] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the high-speed wire harness assembly method based on intelligent algorithm detection described above.

[0019] To address the problems described in the background art, this invention receives a wire harness assembly signal, confirms the wire harness specifications based on the signal, and identifies multiple original conductors based on the specifications. For each of these original conductors, the following operations are performed: end-face image acquisition is performed to obtain a conductor image; the insulation layer thickness is confirmed based on the image; and the original conductor is stripped using a laser wire stripper with the insulation layer thickness and a pre-confirmed measurement, resulting in a qualified stripped conductor. This invention demonstrates that real-time image analysis precisely controls the stripping depth, effectively avoiding core damage or insulation residue issues caused by uneven insulation layer thickness or operational errors in traditional processes. Next, this invention performs core inspection on the qualified stripped conductors, obtaining a core inspection report. This report indicates whether the conductor is qualified or unqualified. Multiple core inspection reports are then compiled. This invention, through automated core inspection and real-time sorting, accurately removes damaged or unqualified conductors generated during the stripping process before crimping, preventing unqualified conductors from entering subsequent processes. Furthermore, this invention identifies multiple qualified wires based on multiple core inspection reports, and uses these qualified wires for terminal crimping to obtain multiple crimped wires. It is evident that this embodiment of the invention improves the electrical reliability and mechanical strength of the crimping process by selecting qualified wires, ensuring good and stable performance of the high-speed harness. Further, this invention identifies multiple qualified crimped wires by verifying their crimping quality, and then bundles these qualified crimped wires into a harness, obtaining multiple bundled harnesses. It is evident that this embodiment of the invention, through automated verification and screening of crimping quality, ensures that reliable wires enter the bundling stage, thereby guaranteeing the overall safety and durability of the high-speed harness. Therefore, this invention can solve the problem of low finished product yield caused by insufficient wire stripping accuracy and poor crimping quality during high-speed harness assembly. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a high-speed wire harness assembly method based on intelligent algorithm detection, provided in an embodiment of the present invention. Figure 2 This is a functional block diagram of a high-speed wire harness assembly system based on intelligent algorithm detection provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device that implements the high-speed wire harness assembly method based on intelligent algorithm detection, according to an embodiment of the present invention.

[0021] Explanation of reference numerals in the attached figures: 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0022] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0024] This application provides a high-speed wire harness assembly method based on intelligent algorithm detection. The execution entity of the high-speed wire harness assembly method based on intelligent algorithm detection includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the high-speed wire harness assembly method based on intelligent algorithm detection can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0025] Reference Figure 1 The diagram shown is a flowchart illustrating a high-speed wire harness assembly method based on intelligent algorithm detection according to an embodiment of the present invention. In this embodiment, the high-speed wire harness assembly method based on intelligent algorithm detection includes: S1. Receive the wire harness assembly signal, determine the wire harness specifications based on the wire harness assembly signal, and determine multiple original wires based on the wire harness specifications.

[0026] It should be explained that the wire harness assembly signal is an instruction used to initiate the assembly process of a high-speed wire harness. This signal includes the wire harness specifications. A high-speed wire harness is a cable assembly used to transmit high-speed digital signals. The wire harness specifications, obtained through the wire harness assembly signal, are a set of parameters characterizing the technical requirements of that batch of high-speed wire harnesses. Examples include stripping length and terminal specifications. The raw conductors are insulated conductors retrieved from the conductor warehouse that meet the stated wire harness specifications and have not undergone any processing. The conductor warehouse is a warehouse storing insulated conductors of various specifications.

[0027] S2. Perform the following operation on each of the multiple original conductors: acquire end face images of the original conductors to obtain conductor images, and determine the insulation layer thickness based on the conductor images.

[0028] It should be explained that end-face image acquisition is the process of taking a vertical photograph of the cross-section of one end of the original conductor using an industrial camera. The conductor image is an image of the cross-section of one end of the original conductor, used to measure the thickness of the insulation layer. The insulation layer thickness is the thickness of the insulating material covering the original conductor.

[0029] S3. Using the insulation layer thickness and a pre-confirmed laser wire stripper, the original wire is stripped to obtain a qualified stripped wire.

[0030] It should be explained that the process of using an insulation layer thickness and a pre-confirmed laser wire stripping machine to strip the original wire to obtain a qualified stripped wire includes: Using a laser wire stripper, the insulation layer thickness, and a preset stripping length, the original wire is laser stripped to obtain a stripped wire. Obtain the image of the stripped wire; A pre-built edge detection algorithm is used to detect the stripping length of a stripped wire image, and the detected length is obtained. The stripping deviation is calculated using the detection length and the stripping length. The wire stripping deviation is compared with a preset deviation threshold. If the wire stripping deviation is less than the deviation threshold, the wire stripped is considered a qualified wire stripped. If the stripping deviation is greater than or equal to the deviation threshold, the stripped wire is treated as the original wire, and the process returns to the step of acquiring the end face image of the original wire until the stripping deviation is less than the deviation threshold, at which point the stripped wire is considered a qualified stripped wire.

[0031] Furthermore, a laser wire stripper is an automated device that uses laser energy to precisely ablate the insulation layer of the original wire without damaging the internal conductor. Laser wire strippers are existing technology and will not be elaborated further here. The stripping length is the length of the insulation layer that needs to be removed from the original wire, obtained from the wire bundle specifications. Laser wire stripping is the process of stripping the original wire according to the stripping length using a laser wire stripper. The stripped wire is the wire whose insulation layer has been partially removed after laser stripping, exposing the internal conductor. The stripped wire image is an image obtained by taking pictures of the stripped wire along its length using an industrial camera. The edge detection algorithm is a computer vision algorithm that automatically identifies the boundary between the insulation layer and the conductor of the stripped wire. Optionally, the Canny operator is used as the edge detection algorithm. Stripping length detection is the process of measuring the actual length of insulation layer removed by analyzing the stripped wire image. The detected length is the length of the stripped insulation layer actually measured by the edge detection algorithm. The stripping deviation is the absolute difference between the detected length and the preset stripping length. The deviation threshold is the maximum allowable stripping length error; a stripping deviation exceeding this threshold is considered unqualified. For example, 0.5 mm. A qualified stripped conductor is a stripped finished product whose stripping deviation is within the allowable range and meets the assembly requirements.

[0032] S4. Perform core testing on qualified stripped conductors to obtain a core testing report, which includes whether the conductor is qualified or unqualified. Summarize the core testing reports to obtain multiple core testing reports, and confirm multiple qualified conductors based on the multiple core testing reports.

[0033] It should be explained that the core testing of qualified stripped conductors, and the resulting core testing report, includes: Surface quality is tested on qualified stripped conductors to obtain a surface quality score. If the surface quality score is less than the preset surface quality score threshold, a core inspection report is obtained, and the core inspection report is unqualified. If the surface quality score is greater than or equal to the surface quality score threshold, the end face image of the qualified stripped wire is acquired using a pre-confirmed ring low-angle light source. Extract multiple closed edge points using end-face images; The optimal circle is obtained by performing least-squares circle fitting using multiple closed edge points. Distance deviations are calculated using multiple closed edge points and the optimal circle, resulting in multiple distance deviations, each corresponding to a closed edge point. Obtain the maximum distance deviation among multiple distance deviations, and use the maximum distance deviation to calculate roundness; Obtain the core silhouette of a qualified stripped conductor; Thresholding is applied to the wire core silhouette to obtain a binary image; Use binary images to obtain the outer contour image and inner hole image of the wire core; The area of ​​the outer contour of the wire core is obtained from the outer contour image of the wire core, and the area of ​​the inner hole is obtained from the inner hole image. The proportion of the wire core is calculated using the outer contour area of ​​the wire core and the preset nominal area; The proportion of the inner hole is calculated using the outer contour area of ​​the wire core and the area of ​​the inner hole. The roundness is compared with the preset roundness threshold, the core proportion is compared with the preset core proportion threshold, and the inner hole proportion is compared with the preset inner hole proportion threshold. If the roundness is greater than or equal to the roundness threshold, the core proportion is greater than or equal to the core proportion threshold, and the inner hole proportion is less than the inner hole proportion threshold, then a core inspection report is obtained, and the core inspection report is qualified. If the roundness is less than the roundness threshold, the core proportion is less than the core proportion threshold, or the internal hole proportion is greater than or equal to the internal hole proportion threshold, then a core inspection report is obtained, and the core inspection report is unqualified.

[0034] Furthermore, a ring-shaped low-angle light source is an illumination device installed around a camera lens to illuminate the end face of a qualified stripped wire at a very small angle (e.g., 0-15 degrees). The purpose is to effectively highlight the contour and unevenness of the end face (surface of the wire core) of the qualified stripped wire. The end face image is an image acquired under ring-shaped low-angle light source illumination, clearly showing the shape and texture features of the end face of the qualified stripped wire. Closed edge points are pixels extracted from the end face image that form the outer contour of the wire core and are connected end-to-end. Optionally, the Canny operator is used as the algorithm for extracting the closed edge points. Least squares circle fitting is a method to find the optimal circle by minimizing the sum of the squares of the distances from all closed edge points to the fitted circle. Optionally, the least squares method is used as the least squares circle fitting method. The optimal circle is the circle that is geometrically closest to all closed edge points, calculated by the least squares circle fitting algorithm, defined by its center coordinates and radius. Optionally, the image coordinate system is used as the coordinate system for the center coordinates. The center coordinates are the pixel coordinates of the center of the optimal circle. Distance deviation calculation is the process of calculating the perpendicular distance from each closed edge point to the circumference of the optimal circle. Distance deviation is the shortest straight-line distance from the closed edge point to the circumference of the optimal circle along the line connecting the closed edge point to its center; it quantifies the degree of deviation between the closed edge point and the optimal circle. The perpendicular distance is the shortest distance from the closed edge point to the circumference of the optimal circle. The maximum distance deviation is the largest of the multiple distance deviations, reflecting the most prominent defect on the outer contour of the wire core.

[0035] Understandably, roundness is a parameter used to quantify how close a circle is to an ideal circle. A smaller roundness value indicates a circle is closer to the ideal circle. The formula for calculating roundness is as follows:

[0036] in, Indicates roundness, Indicates the maximum distance deviation. This represents the radius of the optimal circle.

[0037] Furthermore, the wire core silhouette is an image captured under specific lighting (e.g., backlight) and a background (transparent plate), where the end face of the wire core appears as a high-contrast black and white area, facilitating contour and hole analysis. In the wire core silhouette, the solid portion of the wire core appears dark (low grayscale value), while the background and internal holes appear bright (high grayscale value). Thresholding segmentation is the process of separating the wire core from the background and holes in the wire core silhouette using a set grayscale threshold (e.g., 128). The binary image, after thresholding segmentation, has only two pixel values: 0 (black, representing the background) or 255 (white, representing the foreground). White represents the background, including the outer area of ​​the wire core and internal holes, while black represents the foreground, i.e., the solid metal portion of the wire core. The wire core outer contour image is an image of a closed black area representing the overall outer boundary of the wire core, extracted from the binary image. The internal hole image is an image of a closed white area located inside the black outer contour of the wire core and surrounded by black areas, identified from the binary image, characterizing material deficiencies or voids in the wire core.

[0038] Understandably, the surface rating threshold is the lower limit used to determine whether the conductor surface quality of a qualified stripped conductor meets the usage requirements. For example, 70. The core outer contour area is the total pixel area (the sum of all black pixels) enclosed by the core outer contour image, representing the observed core cross-sectional area. The inner hole area is the total pixel area (the sum of all enclosed white pixels) of all inner hole images, representing the total missing area inside the core cross-section. The nominal area is the ideal cross-sectional area calculated based on the core design specifications (such as nominal diameter), serving as a theoretical benchmark. The core percentage is the ratio of the core outer contour area to the nominal area, used to evaluate the fullness of the core material filling. The formula for calculating the core percentage is as follows:

[0039] in, Indicates the percentage of wire cores. Indicates the area of ​​the outer contour of the wire core. Indicates the nominal area.

[0040] Furthermore, the internal void ratio is the ratio of the internal void area to the outer contour area of ​​the wire core, used to assess the density or porosity defects inside the wire core. The formula for calculating the internal void ratio is as follows:

[0041] in, Indicates the percentage of internal voids. This indicates the area of ​​the internal cavity.

[0042] Understandably, the roundness threshold is the upper limit for acceptable roundness. For example, 1.5% means that if the calculated roundness exceeds the threshold, it is judged as not round. The core proportion threshold is the lower limit for acceptable core proportion. For example, 95% means that if the calculated core proportion is lower than this value, it is judged as insufficient cross-sectional area. The internal hole proportion threshold is the upper limit for acceptable internal hole proportion. For example, 2% means that if the calculated internal hole proportion exceeds this value, it is judged as excessive internal hole defects. The core inspection report is used to determine whether the qualified stripped conductor meets the requirements for subsequent processing. The core inspection report includes "qualified" or "unqualified". "Qualified" means that all parameters of the core (surface quality score, roundness, core proportion, and internal hole proportion) meet the preset standards and comply with the quality requirements. "Unqualified" means that at least one of the parameters of the core (surface quality score, roundness, core proportion, and internal hole proportion) fails to meet the preset standard, indicating a quality defect.

[0043] It should be explained that the surface quality inspection of qualified stripped wires to obtain a surface quality score includes: Surface images of qualified stripped conductors are acquired to obtain conductor surface images; The conductor surface image is filtered and denoised to obtain a denoised conductor surface image; The noise-reduced conductor surface image is converted to grayscale to obtain a grayscale conductor surface image; Edge contours are extracted from grayscale conductor surface images to obtain the area of ​​scratch contours; Calculate the local binary mode variance map using grayscale conductor surface images; The local binary pattern variance map is binarized and segmented to obtain the potential ablation region; Obtain the scorch area of ​​the potential scorch zone; The surface quality score is calculated using the scratch contour area and the burned area. The formula for calculating the surface quality score is as follows:

[0044] in, Indicates the surface quality score. This represents the preset scratch weight coefficient. Indicates the area of ​​the scratch outline. This represents the preset scorching weight coefficient. Indicates the area burned.

[0045] Furthermore, surface image acquisition involves using a high-resolution industrial camera to photograph the exposed conductor in a qualified stripped wire under constant LED ring light illumination, perpendicular to the axis of the wire. The conductor surface image, obtained through surface image acquisition, contains information about surface texture, scratches, burns, and other defects in the exposed conductor of the qualified stripped wire. Filtering and denoising is the process of suppressing noise in the conductor surface image. Optionally, Gaussian filtering is used as the filtering and denoising method. The denoised conductor surface image is the conductor surface image after filtering and denoising. Grayscale conversion is the process of converting the denoised conductor surface image into a grayscale image. The grayscale conductor surface image is the grayscale image obtained after grayscale conversion of the denoised conductor surface image. Edge contour extraction is the process of identifying and outlining the boundaries of linear defects (scratches) from the grayscale conductor surface image and calculating their pixel area. Optionally, the Canny operator is used as the edge contour extraction method. The scratch contour area is the total pixel area enclosed by the boundaries of all identified scratch defects, obtained through edge contour extraction, and is used to quantify the degree of mechanical damage to the conductor surface.

[0046] Understandably, the local binary pattern variance map is calculated for each pixel in the grayscale conductor surface image. Within its circular neighborhood (radius R=2, number of sampling points P=8), the local binary pattern value is calculated, and then the variance of the local binary pattern value is calculated within a 7×7 sliding window. This generates a variance distribution map of the same size as the grayscale conductor surface image, used to characterize the degree of local texture anomalies. Optionally, the local binary pattern is used as the calculation method for the binary pattern variance map. Binary segmentation marks regions with variance values ​​higher than a segmentation threshold as foreground, where the adaptive threshold window size is 32×32. The white areas in the resulting binary image after segmentation are the potential burning regions. Optionally, the Otsu binarization method is used as the binarization segmentation method. The potential burning region is all connected regions marked as foreground (white) in the binary image obtained after binarization segmentation. The potential burning region corresponds to the texture anomalies on the conductor surface caused by overheating due to improper laser energy, characterizing the potential location and extent of burning defects. The scorch area is the total pixel area of ​​all potential scorch regions, used to quantify the size of texture anomalies on the conductor surface caused by thermal damage. The surface quality score is a comprehensive quantitative value calculated based on the scratch contour area and the scorch area. The surface quality score is deducted from an initial maximum of 100 points based on the size of the scratch contour area and the scorch area; a lower final score indicates worse conductor surface quality. The scratch weight coefficient defines the quality deduction value per unit area for scratch defects in the surface quality score calculation, reflecting the relative importance of scratch-type mechanical damage in quality assessment. The scorch weight coefficient defines the quality deduction value per unit area for scorch defects in the surface quality score calculation, reflecting the relative importance of scorch-type thermal damage in quality assessment. The setting of the scratch weight coefficient and the scorch weight coefficient needs to be finalized through regression analysis of experimental data (such as the correlation between samples with different defect levels and their failure in subsequent processes or reliability tests) to ensure that the surface quality score calculation formula can accurately predict the actual quality level of the conductor.

[0047] Furthermore, identifying multiple qualified conductors based on multiple conductor test reports means that qualified stripped conductors corresponding to conductor test reports that are qualified in multiple conductor test reports are considered qualified conductors, while qualified stripped conductors corresponding to conductor test reports that are unqualified in multiple conductor test reports are excluded.

[0048] S5. Use multiple qualified wires to crimp the terminals to obtain multiple crimped wires.

[0049] It should be explained that the process of using multiple qualified wires to crimp terminals, resulting in multiple crimped wires, includes: For each of the multiple qualified conductors, perform the following operation: The qualified wires are transported to the pre-confirmed crimping station, and the qualified wires are mechanically positioned using the pre-confirmed guide groove to obtain the ready-to-use wires. Obtain wire harness terminals; The wire harness terminals are transported to the crimping station, where a pre-confirmed industrial camera is used to capture images of the wire harness terminals, thus obtaining terminal images. The overall pose deviation is calculated using the terminal image and the pre-constructed reference template image; The overall pose deviation is compared with a preset pose deviation threshold. If the overall pose deviation is less than the pose deviation threshold, the wire harness terminal is used as a standby terminal. If the overall pose deviation is greater than or equal to the pose deviation threshold, a pose adjustment command is generated. The pose adjustment command and the pre-confirmed calibration nozzle are used to calibrate the wire harness terminal to obtain a calibrated terminal. The calibrated terminal is used as the wire harness terminal, and the process returns to the step of using the pre-confirmed industrial camera to acquire images of the wire harness terminal until the overall pose deviation is less than the pose deviation threshold. The wire harness terminal is then used as a standby terminal. The wire to be used and the terminal to be used are crimped together to obtain a crimped wire; By combining the crimped wires, multiple crimped wires are obtained.

[0050] Furthermore, the crimping station is the working position used to crimp qualified wires to wire harness terminals. The guide groove is a mechanical structure with a specific shape and size used to guide and constrain the exposed conductor portion of the qualified wire before crimping, ensuring proper crimping with the wire harness terminal. Mechanical positioning is the process of fixing the end of the qualified wire in a predetermined position and angle in three-dimensional space through the guide groove. The ready-to-use wire is the qualified wire after mechanical positioning. The wire harness terminal is a wiring termination used to transmit electrical signals or conduct electricity. The terminal image is a digital image containing the shape, position, and angle information of the wire harness terminal, captured by an industrial camera at the crimping station, used to analyze the current pose of the wire harness terminal. The pose deviation threshold is the maximum allowable comprehensive pose deviation value used to determine whether the wire harness terminal pose meets the crimping requirements. For example, it can be set to a position deviation of 2 pixels and an angle deviation of 1.5 degrees.

[0051] Understandably, a ready-to-use terminal is a wire harness terminal whose positional deviation is confirmed to be within the allowable range and suitable for crimping. The attitude adjustment command is a control signal generated based on the comprehensive attitude deviation, containing specific adjustment direction and amount, used to drive a calibration nozzle to correct the terminal's attitude. The calibration nozzle is an actuator that uses compressed air to generate precise, controllable pulsed airflow to blow or correct incorrectly positioned wire harness terminals. Optionally, an air nozzle is used as the calibration nozzle. Correction is the process of fine-tuning the spatial position and angle of the wire harness terminal by applying pulsed airflow through the calibration nozzle according to the attitude adjustment command. A corrected terminal is a wire harness terminal whose attitude has been improved after the correction operation. Crimping is the process at the crimping station where pressure is applied to the ready-to-use terminal using a crimping die, causing it to plastically deform and tightly wrap around a qualified wire, forming a strong mechanical and electrical connection. A crimped wire is a complete electrical connection assembly formed after the ready-to-use wire and the ready-to-use terminal are crimped together.

[0052] It should be explained that the calculation of the overall pose deviation using the terminal image and the pre-constructed reference template image includes: The terminal image is preprocessed to obtain a preprocessed terminal image; Template matching is performed using the preprocessed terminal image and the reference template image to obtain the matched terminal image; Obtain multiple reference feature points from the matching terminal image; The coordinates of multiple reference feature points are obtained using multiple reference feature points and a pre-constructed rectangular coordinate system; Multiple reference feature points are obtained based on the coordinates of multiple reference feature points, and the coordinates of multiple reference feature points are obtained. Among them, the reference feature points and the reference feature points correspond one-to-one. A rigid transformation matrix is ​​constructed using the coordinates of multiple reference feature points and multiple reference feature points. The rigid transformation matrix includes a translation vector and a rotation matrix. The positional deviation is calculated using the translation vector. The attitude deviation angle is calculated using the rotation matrix. The overall pose deviation is calculated using the position deviation amount and the attitude deviation angle.

[0053] Further, preprocessing involves enhancing the acquired raw terminal images (including grayscale conversion, filtering and noise reduction, and contrast enhancement) to improve image quality and facilitate subsequent feature extraction. The preprocessed terminal image is the improved terminal image obtained after preprocessing. The reference template image is a clear image of the wire harness terminal acquired in a standard pose (without deviations in position or angle), serving as an ideal reference for calculating the current terminal pose deviation. Template matching uses the reference template image as a sliding window, systematically translating (and extending to rotation and scaling) within the preprocessed terminal image. A similarity measurement algorithm (e.g., stereo vision matching) is used to calculate the matching degree between the reference template image template and the corresponding regions of the preprocessed terminal image, ultimately determining the optimal matching position and rotation angle. The fundamental purpose of this process is to achieve rapid coarse localization of the wire harness terminals, laying the foundation for subsequent precise measurements. The matched terminal image is a sub-image cropped from the preprocessed terminal image, with the same size as the reference template image, based on the optimal matching position and rotation angle output from the reference template image matching. Reference feature points are key points extracted from the matched terminal images that can stably characterize the position and orientation of the terminals, such as corner points, center points, or marker points with unique shapes of the wire harness terminal outline.

[0054] Understandably, the Cartesian coordinate system is a two-dimensional image coordinate system established with the top-left corner of the matching terminal image as the origin O, the positive X-axis pointing horizontally to the right, and the positive Y-axis pointing vertically downwards. The coordinate unit is pixels, which are later converted to the physical unit millimeters through camera calibration parameters. The reference feature point coordinates are the coordinates of the reference feature point in the Cartesian coordinate system. The reference feature point is the point corresponding to the reference feature point in the reference template image. The reference feature point coordinates are the coordinates of the reference feature point in the Cartesian coordinate system. The positional deviation is determined by the translation vector in the rigid transformation matrix (…). , The calculated overall translational magnitude of the wire harness terminal relative to its standard position in the X and Y directions, in pixels, is given below. The formula for calculating the positional deviation is as follows:

[0055] in, This indicates the positional deviation. This indicates the amount of translation of the wire harness terminal in the X-axis direction. This indicates the amount of translation of the wire harness terminal in the Y-axis direction.

[0056] Furthermore, the attitude deviation angle is the rotation angle of the harness terminal relative to the standard attitude about the origin of the coordinate system, calculated using the rotation matrix in the rigid transformation matrix. The unit is degrees. The comprehensive pose deviation is a comprehensive evaluation index that combines the positional deviation and attitude deviation angle into a single scalar value, used to quantify the pose accuracy of the overall measurement. It is used to unify the dimensions and adjust the weights of the two in the overall deviation. The formula for calculating the comprehensive pose deviation is as follows:

[0057] in, Indicates the overall pose deviation. This represents the position normalization coefficient. This represents the angle normalization coefficient, used to standardize the dimensions and adjust the weights of position deviation and attitude deviation angles in the overall pose deviation. This indicates the attitude deviation angle.

[0058] It should be explained that the construction of the rigid transformation matrix using multiple reference feature point coordinates and multiple reference feature point coordinates includes: Calculate the coordinates of the reference centroid using the coordinates of multiple reference feature points; Calculate the reference centroid coordinates using the coordinates of multiple reference feature points; Using the reference centroid, the coordinates of each of the multiple reference feature points are centered to obtain multiple centered reference feature point coordinates, where the centered reference feature point coordinates correspond one-to-one with the reference feature point coordinates. Multiple centered reference feature point coordinates are obtained using the reference centroid coordinates and multiple reference feature point coordinates, wherein the coordinates of the centered reference feature point correspond one-to-one with the coordinates of the reference feature point. A covariance matrix is ​​constructed using the coordinates of multiple centralized benchmark feature points and multiple centralized reference feature points; Singular value decomposition is performed on the covariance matrix to obtain the left singular vector matrix and the right singular vector matrix; Calculate the rotation matrix using the left and right singular vector matrices; Calculate the translation vector using the reference centroid coordinates, the datum centroid coordinates, and the rotation matrix; A rigid transformation matrix is ​​constructed using the rotation matrix and translation vector.

[0059] Furthermore, the reference barycenter coordinates are the center point coordinates obtained by taking the arithmetic mean of the coordinates of multiple reference feature points, and are used as the reference center to eliminate the effects of translation. The reference barycenter coordinates are the center point coordinates obtained by taking the arithmetic mean of the coordinates of multiple reference feature points, and are used as the central reference for the standard pose. The centered reference feature point coordinates are the coordinates obtained by subtracting the reference barycenter coordinates from the reference feature point coordinates. The centered reference feature point coordinates are the coordinates obtained by subtracting the reference barycenter coordinates from the reference feature point coordinates.

[0060] For example, the coordinates of the reference feature point are ( , The reference centroid coordinates are ( , Then the coordinates of the centered reference feature point are ( , ).

[0061] Understandably, the covariance matrix is ​​a matrix used to describe the correlation between the coordinates of multiple centralized baseline feature points and the coordinates of multiple centralized reference feature points. The formula for calculating the covariance matrix is ​​as follows:

[0062] in, Represents the covariance matrix. This represents a structure constructed from the coordinates of multiple centralized reference feature points. matrix, Represents a structure constructed from the coordinates of multiple centralized reference feature points. matrix, This represents the number of centralized baseline feature points. This indicates the matrix transpose.

[0063] For example, constructed from the coordinates of multiple centralized reference feature points. The matrix is ​​shown below:

[0064] in, Indicates the first The x-coordinate of a centralized reference feature point. Indicates the first The ordinate of each centralized reference feature point, and Constructed from the coordinates of multiple centralized reference feature points. The matrix is ​​shown below:

[0065] in, Indicates the first The x-coordinate of a centralized reference feature point. Indicates the first The ordinate of a centralized reference feature point.

[0066] Furthermore, singular value decomposition (SVD) is a numerical algorithm for matrix decomposition of the covariance matrix H. Optionally, the Jacobi iteration method is used as the SVD method. The left singular vector matrix is ​​an orthogonal matrix obtained after SVD, used to describe the principal orientations of multiple reference feature points after transformation. The right singular vector matrix is ​​an orthogonal matrix obtained after SVD, used to describe the principal orientations of multiple reference feature points. The rotation matrix is ​​a two-dimensional orthogonal matrix calculated using the left and right singular vector matrices, used to describe the rotational changes required from the reference point set to the reference point set. The formula for calculating the rotation matrix is ​​as follows:

[0067] in, Represents the rotation matrix. Describes a right singular vector matrix. This represents the transpose of the left singular vector matrix.

[0068] Understandably, a translation vector is a two-dimensional vector used to describe the required translational motion after the wire harness terminal has been rotated. The formula for calculating the translation vector is as follows:

[0069] in, Represents the translation vector. Indicates the reference centroid coordinates. Indicates the reference centroid coordinates.

[0070] Understandably, a rigid transformation matrix is ​​a matrix consisting of rotation matrices and translation vectors, used to perform rotations and translations simultaneously within a unified mathematical framework.

[0071] S6. The crimping quality of multiple crimped wires is checked to obtain multiple qualified crimped wires.

[0072] It should be explained that the process of verifying the crimping quality of multiple crimped wires to obtain multiple qualified crimped wires includes: Perform the following operation on each of the multiple crimped wires: Obtain an image of the terminal area of ​​the crimped wire; The terminal area image is smoothed and filtered to obtain a noise-reduced image; Based on the pre-confirmed qualified terminal image, the noise-reduced image is used to locate the terminal to obtain the located image; Global illumination compensation is performed on the positioned image using the qualified terminal image to obtain the compensated image; Image difference processing is performed using the compensated image and the qualified terminal image to obtain the difference image; The difference image is binarized to obtain a binary difference image; The defect area is calculated using a binary difference image. The defect area is then compared with a preset defect area threshold. If the defect area is less than the defect area threshold, the crimped wire is considered a qualified crimped wire. By summarizing the qualified crimped wires, multiple qualified crimped wires are obtained.

[0073] Furthermore, the terminal area image is an image captured by an industrial camera, containing the wire harness terminals and their crimping areas in the crimped wires. Smoothing filtering is a process of smoothing the terminal area image to suppress image noise. Optionally, Gaussian filtering is used as the smoothing filtering method. The denoised image is the terminal area image obtained after smoothing filtering, where noise is effectively suppressed. The qualified terminal image is a terminal area image captured under standard lighting conditions without any visible defects, serving as a benchmark template for inspection. Image difference processing involves calculating pixel-level differences (the difference in grayscale value of each corresponding pixel) between the compensated image and the qualified terminal image, obtaining multiple differences. These differences are compared with a preset difference threshold (e.g., 30), and the grayscale value of pixels with differences below the threshold is set to 0 to highlight the difference area between the image to be inspected and the standard template. The difference image is the image obtained through image difference processing. Binarization is the process of converting the difference image into an image containing only black and white pixel values ​​by setting a threshold (e.g., 128), thereby separating the defect area from the background. This is for the purpose of facilitating subsequent statistical analysis. The binary difference image is an image obtained after binarization, where white areas represent defects and black areas represent the background. The defect area is the total area of ​​all white pixels in the binary difference image, used to quantify the degree of appearance abnormality of the terminal area. The defect area threshold is a preset upper limit value for the defect area based on actual quality requirements (e.g., 200 pixels), used as a critical standard to determine whether the crimped wire is qualified. Qualified crimped wires are those that have passed the above screening process and whose defect area is less than the defect area threshold, thus meeting the quality requirements.

[0074] It should be explained that the step of using the qualified terminal image to perform global illumination compensation on the positioned image to obtain the compensated image includes: The system acquires multiple actual grayscale values ​​of the image after positioning and multiple template grayscale values ​​of the qualified terminal image, wherein the actual grayscale values ​​correspond one-to-one with the template grayscale values. Calculate the mean and standard deviation of the actual grayscale using multiple actual grayscale values; Calculate the mean gray level and standard deviation of the template gray level using multiple template gray level values; For each of the multiple actual grayscale values, perform the following operation: The compensated gray value is calculated using the actual gray value, the actual gray mean, the actual gray standard deviation, the template gray mean, and the template gray standard deviation. The formula for calculating the compensated gray value is shown below:

[0075] in, Indicates the compensation standard deviation, Indicates the standard deviation of template grayscale. Indicates the actual grayscale standard deviation. This represents the actual grayscale value. This represents the average grayscale value of the template. This represents the actual average gray level. By summing the aforementioned compensation grayscale values, multiple compensation grayscale values ​​are obtained; The multiple compensated grayscale values ​​are mapped to the localized image to obtain the compensated image.

[0076] Furthermore, the actual grayscale value is the grayscale value of a specific pixel in the positioned image. The template grayscale value is the grayscale value of the pixel in the qualified terminal image corresponding to the position in the positioned image. The actual grayscale mean is the arithmetic mean of the grayscale values ​​of all pixels in the positioned image. The actual grayscale standard deviation is the standard deviation of the grayscale values ​​of all pixels in the positioned image. The template grayscale mean is the arithmetic mean of the grayscale values ​​of all pixels in the qualified terminal image. The template grayscale standard deviation is the standard deviation of the grayscale values ​​of all pixels in the qualified terminal image. The compensated grayscale value is the grayscale value of the corresponding pixel obtained after calculation. The purpose is to ensure that the grayscale distribution (mean and standard deviation) of the positioned image is consistent with that of the qualified terminal image. Mapping is the process of remapping the calculated compensated grayscale values ​​to the positioned image according to the position of their corresponding pixels. The compensated image is an image after global illumination compensation processing, the purpose of which is to effectively eliminate the uneven illumination caused by factors such as light source fluctuations and differences in reflection on the terminal surface, providing a reliable reference alignment for subsequent inspection.

[0077] S7. Bundle multiple qualified crimped wires together to obtain multiple bundled wires.

[0078] It should be explained that wire harness bundling is the process of arranging and branching multiple qualified crimped wires according to a predetermined geometric layout and topology, and then mechanically fixing them using bundling tape, sleeves, or adhesive tape, thereby integrating them into a wire harness with a uniform structure. The geometric layout and topology can be obtained from the wire harness specifications and will not be elaborated upon here. A bundled wire harness is an integrated wire harness that conforms to the wire harness specifications after bundling.

[0079] To address the problems described in the background art, this invention receives a wire harness assembly signal, confirms the wire harness specifications based on the signal, and identifies multiple original conductors based on the specifications. For each of these original conductors, the following operations are performed: end-face image acquisition is performed to obtain a conductor image; the insulation layer thickness is confirmed based on the image; and the original conductor is stripped using a laser wire stripper with the insulation layer thickness and a pre-confirmed measurement, resulting in a qualified stripped conductor. This invention demonstrates that real-time image analysis precisely controls the stripping depth, effectively avoiding core damage or insulation residue issues caused by uneven insulation layer thickness or operational errors in traditional processes. Next, this invention performs core inspection on the qualified stripped conductors, obtaining a core inspection report. This report indicates whether the conductor is qualified or unqualified. Multiple core inspection reports are then compiled. This invention, through automated core inspection and real-time sorting, accurately removes damaged or unqualified conductors generated during the stripping process before crimping, preventing unqualified conductors from entering subsequent processes. Furthermore, this invention identifies multiple qualified wires based on multiple core inspection reports, and uses these qualified wires for terminal crimping to obtain multiple crimped wires. It is evident that this embodiment of the invention improves the electrical reliability and mechanical strength of the crimping process by selecting qualified wires, ensuring good and stable performance of the high-speed harness. Further, this invention identifies multiple qualified crimped wires by verifying their crimping quality, and then bundles these qualified crimped wires into a harness, obtaining multiple bundled harnesses. It is evident that this embodiment of the invention, through automated verification and screening of crimping quality, ensures that reliable wires enter the bundling stage, thereby guaranteeing the overall safety and durability of the high-speed harness. Therefore, this invention can solve the problem of low finished product yield caused by insufficient wire stripping accuracy and poor crimping quality during high-speed harness assembly.

[0080] like Figure 2 The diagram shown is a functional block diagram of a high-speed wire harness assembly system based on intelligent algorithm detection provided in an embodiment of the present invention.

[0081] The high-speed wire harness assembly system 100 based on intelligent algorithm detection described in this invention can be installed in electronic devices. Depending on the functions implemented, the high-speed wire harness assembly system 100 based on intelligent algorithm detection may include an original wire stripping module 101, a wire core quality detection module 102, a wire terminal crimping module 103, and a qualified wire bundling module 104. The module described in this invention can also be called a unit, referring to a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0082] The original wire stripping module 101 is used to receive the wire harness assembly signal and confirm the wire harness specifications based on the wire harness assembly signal. Multiple original conductors were identified based on the wire harness specifications; Perform the following operation on each of the multiple original conductors: The end face image of the original conductor is acquired to obtain the conductor image; The insulation layer thickness was determined based on the wire image; The original conductor is stripped using a laser wire stripper with pre-confirmed insulation layer thickness and a pre-determined insulation layer thickness to obtain a qualified stripped conductor. The core quality inspection module 102 is used to inspect the core of qualified stripped conductors and obtain a core inspection report, wherein the core inspection report includes whether it is qualified or unqualified. By summarizing the aforementioned core inspection reports, multiple core inspection reports are obtained; The wire terminal crimping module 103 is used to confirm multiple qualified wires based on multiple wire core test reports; Multiple qualified wires are used to crimp the terminals to obtain multiple crimped wires; The crimping quality of multiple crimped wires was checked, and multiple qualified crimped wires were obtained. The qualified wire bundling module 104 is used to bundle multiple qualified crimped wires together to obtain multiple bundled wire bundles.

[0083] In detail, the modules in the high-speed wire harness assembly system 100 based on intelligent algorithm detection described in this embodiment of the invention employ the same methods as described above during use. Figure 1 The method used is the same as the high-speed wire harness assembly method based on intelligent algorithm detection described in the article, and can produce the same technical effect, so it will not be repeated here.

[0084] like Figure 3 The diagram shown is a structural schematic of an electronic device that implements a high-speed wire harness assembly method based on intelligent algorithm detection, according to an embodiment of the present invention.

[0085] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and capable of running on the processor 10, such as a high-speed wire harness assembly method program based on intelligent algorithm detection.

[0086] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as the code of a high-speed wire harness assembly method program based on intelligent algorithm detection, but also to temporarily store data that has been output or will be output.

[0087] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a high-speed wire harness assembly method program based on intelligent algorithm detection) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0088] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0089] Figure 3 Only electronic devices with components are shown; those skilled in the art will understand that... Figure 3The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0090] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management system, thereby enabling functions such as charging management, discharging management, and power consumption management through the power management system. The power supply may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0091] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0092] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0093] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0094] The high-speed wire harness assembly method program based on intelligent algorithm detection, stored in the memory 11 of the electronic device 1, is a combination of multiple instructions. When run in the processor 10, it can achieve the following: Receive the wire harness assembly signal and determine the wire harness specifications based on the wire harness assembly signal; Multiple original conductors were identified based on the wire harness specifications; Perform the following operation on each of the multiple original conductors: The end face image of the original conductor is acquired to obtain the conductor image; The insulation layer thickness was determined based on the wire image; The original conductor is stripped using a laser wire stripper with pre-confirmed insulation layer thickness and a pre-determined insulation layer thickness to obtain a qualified stripped conductor. The core of the qualified stripped conductor is tested to obtain a core test report, which indicates whether it is qualified or unqualified. By summarizing the aforementioned core inspection reports, multiple core inspection reports are obtained; Multiple qualified conductors were confirmed based on multiple conductor test reports; Multiple qualified wires are used to crimp the terminals to obtain multiple crimped wires; The crimping quality of multiple crimped wires was checked, and multiple qualified crimped wires were obtained. Multiple qualified crimped wires were bundled together to obtain multiple bundled wire bundles.

[0095] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0096] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or system capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0097] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following: Receive the wire harness assembly signal and determine the wire harness specifications based on the wire harness assembly signal; Multiple original conductors were identified based on the wire harness specifications; Perform the following operation on each of the multiple original conductors: The end face image of the original conductor is acquired to obtain the conductor image; The insulation layer thickness was determined based on the wire image; The original conductor is stripped using a laser wire stripper with pre-confirmed insulation layer thickness and a pre-determined insulation layer thickness to obtain a qualified stripped conductor. The core of the qualified stripped conductor is tested to obtain a core test report, which indicates whether it is qualified or unqualified. By summarizing the aforementioned core inspection reports, multiple core inspection reports are obtained; Multiple qualified conductors were confirmed based on multiple conductor test reports; Multiple qualified wires are used to crimp the terminals to obtain multiple crimped wires; The crimping quality of multiple crimped wires was checked, and multiple qualified crimped wires were obtained. Multiple qualified crimped wires were bundled together to obtain multiple bundled wire bundles.

[0098] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0099] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0100] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0101] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0102] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or systems stated in a system claim may also be implemented by a single unit or system through software or hardware. The term "second class" is used to indicate names and does not indicate any specific order.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A high-speed wire harness assembly method based on intelligent algorithm detection, characterized in that, The method includes: Receive the wire harness assembly signal and determine the wire harness specifications based on the wire harness assembly signal; Multiple original conductors were identified based on the wire harness specifications; Perform the following operation on each of the multiple original conductors: The end face image of the original conductor is acquired to obtain the conductor image; The insulation layer thickness was determined based on the wire image; The original conductor is stripped using a laser wire stripper with pre-confirmed insulation layer thickness and a pre-determined insulation layer thickness to obtain a qualified stripped conductor. The core of the qualified stripped conductor is tested to obtain a core test report, which indicates whether it is qualified or unqualified. The process of performing core testing on qualified stripped conductors to obtain a core testing report includes: Surface quality is tested on qualified stripped conductors to obtain a surface quality score. If the surface quality score is less than the preset surface quality score threshold, a core inspection report is obtained, and the core inspection report is unqualified. If the surface quality score is greater than or equal to the surface quality score threshold, the end face image of the qualified stripped wire is acquired using a pre-confirmed ring low-angle light source. Extract multiple closed edge points using end-face images; The optimal circle is obtained by performing least-squares circle fitting using multiple closed edge points. Distance deviations are calculated using multiple closed edge points and the optimal circle, resulting in multiple distance deviations, each corresponding to a closed edge point. Obtain the maximum distance deviation among multiple distance deviations, and use the maximum distance deviation to calculate roundness; Obtain the core silhouette of a qualified stripped conductor; Thresholding is applied to the wire core silhouette to obtain a binary image; Use binary images to obtain the outer contour image and inner hole image of the wire core; The area of ​​the outer contour of the wire core is obtained from the outer contour image of the wire core, and the area of ​​the inner hole is obtained from the inner hole image. The proportion of the wire core is calculated using the outer contour area of ​​the wire core and the preset nominal area; The proportion of the inner hole is calculated using the outer contour area of ​​the wire core and the area of ​​the inner hole. The roundness is compared with the preset roundness threshold, the core proportion is compared with the preset core proportion threshold, and the inner hole proportion is compared with the preset inner hole proportion threshold. If the roundness is greater than or equal to the roundness threshold, the core proportion is greater than or equal to the core proportion threshold, and the inner hole proportion is less than the inner hole proportion threshold, then a core inspection report is obtained, and the core inspection report is qualified. If the roundness is less than the roundness threshold, the core proportion is less than the core proportion threshold, or the internal hole proportion is greater than or equal to the internal hole proportion threshold, then a core inspection report is obtained, and the core inspection report is unqualified. By summarizing the aforementioned core inspection reports, multiple core inspection reports are obtained; Multiple qualified conductors were confirmed based on multiple conductor test reports; Multiple qualified wires are used to crimp the terminals to obtain multiple crimped wires; The crimping quality of multiple crimped wires was checked, and multiple qualified crimped wires were obtained. Multiple qualified crimped wires were bundled together to obtain multiple bundled wire bundles.

2. The high-speed wire harness assembly method based on intelligent algorithm detection as described in claim 1, characterized in that, The process of stripping the original conductor using a laser wire stripper with pre-confirmed insulation layer thickness to obtain a qualified stripped conductor includes: Using a laser wire stripper, the insulation layer thickness, and a preset stripping length, the original wire is laser stripped to obtain a stripped wire. Obtain the image of the stripped wire; A pre-built edge detection algorithm is used to detect the stripping length of a stripped wire image, and the detected length is obtained. The stripping deviation is calculated using the detection length and the stripping length. The wire stripping deviation is compared with a preset deviation threshold. If the wire stripping deviation is less than the deviation threshold, the wire stripped is considered a qualified wire stripped. If the stripping deviation is greater than or equal to the deviation threshold, the stripped wire is treated as the original wire, and the process returns to the step of acquiring the end face image of the original wire until the stripping deviation is less than the deviation threshold, at which point the stripped wire is considered a qualified stripped wire.

3. The high-speed wire harness assembly method based on intelligent algorithm detection as described in claim 2, characterized in that, The surface quality inspection of qualified stripped conductors, to obtain a surface quality score, includes: Surface images of qualified stripped conductors are acquired to obtain conductor surface images; The conductor surface image is filtered and denoised to obtain a denoised conductor surface image; The noise-reduced conductor surface image is converted to grayscale to obtain a grayscale conductor surface image; Edge contours are extracted from grayscale conductor surface images to obtain the area of ​​scratch contours; Calculate the local binary mode variance map using grayscale conductor surface images; The local binary pattern variance map is binarized and segmented to obtain the potential ablation region; Obtain the scorch area of ​​the potential scorch zone; The surface quality score is calculated using the scratch contour area and the burned area. The formula for calculating the surface quality score is as follows: in, Indicates the surface quality score. This represents the preset scratch weight coefficient. Indicates the area of ​​the scratch outline. This represents the preset scorching weight coefficient. Indicates the area burned.

4. The high-speed wire harness assembly method based on intelligent algorithm detection as described in claim 3, characterized in that, The method involves crimping terminals using multiple qualified wires to obtain multiple crimped wires, including: For each of the multiple qualified conductors, perform the following operation: The qualified wires are transported to the pre-confirmed crimping station, and the qualified wires are mechanically positioned using the pre-confirmed guide groove to obtain the ready-to-use wires. Obtain wire harness terminals; The wire harness terminals are transported to the crimping station, where a pre-confirmed industrial camera is used to capture images of the wire harness terminals, thus obtaining terminal images. The overall pose deviation is calculated using the terminal image and the pre-constructed reference template image; The overall pose deviation is compared with a preset pose deviation threshold. If the overall pose deviation is less than the pose deviation threshold, the wire harness terminal is used as a standby terminal. If the overall pose deviation is greater than or equal to the pose deviation threshold, a pose adjustment command is generated. The pose adjustment command and the pre-confirmed calibration nozzle are used to calibrate the wire harness terminal to obtain a calibrated terminal. The calibrated terminal is used as the wire harness terminal, and the process returns to the step of using the pre-confirmed industrial camera to acquire images of the wire harness terminal until the overall pose deviation is less than the pose deviation threshold. The wire harness terminal is then used as a standby terminal. The wire to be used and the terminal to be used are crimped together to obtain a crimped wire; By combining the crimped wires, multiple crimped wires are obtained.

5. The high-speed wire harness assembly method based on intelligent algorithm detection as described in claim 4, characterized in that, The calculation of the overall pose deviation using the terminal image and the pre-constructed reference template image includes: The terminal image is preprocessed to obtain a preprocessed terminal image; Template matching is performed using the preprocessed terminal image and the reference template image to obtain the matched terminal image; Obtain multiple reference feature points from the matching terminal image; The coordinates of multiple reference feature points are obtained using multiple reference feature points and a pre-constructed rectangular coordinate system; Multiple reference feature points are obtained based on the coordinates of multiple reference feature points, and the coordinates of multiple reference feature points are obtained. Among them, the reference feature points and the reference feature points correspond one-to-one. A rigid transformation matrix is ​​constructed using the coordinates of multiple reference feature points and multiple reference feature points. The rigid transformation matrix includes a translation vector and a rotation matrix. The positional deviation is calculated using the translation vector. The attitude deviation angle is calculated using the rotation matrix. The overall pose deviation is calculated using the position deviation amount and the attitude deviation angle.

6. The high-speed wire harness assembly method based on intelligent algorithm detection as described in claim 5, characterized in that, The method of constructing a rigid transformation matrix using multiple reference feature point coordinates and multiple reference feature point coordinates includes: Calculate the coordinates of the reference centroid using the coordinates of multiple reference feature points; Calculate the reference centroid coordinates using the coordinates of multiple reference feature points; Using the reference centroid, the coordinates of each of the multiple reference feature points are centered to obtain multiple centered reference feature point coordinates, where the centered reference feature point coordinates correspond one-to-one with the reference feature point coordinates. Multiple centered reference feature point coordinates are obtained using the reference centroid coordinates and multiple reference feature point coordinates, wherein the coordinates of the centered reference feature point correspond one-to-one with the coordinates of the reference feature point. A covariance matrix is ​​constructed using the coordinates of multiple centralized benchmark feature points and multiple centralized reference feature points; Singular value decomposition is performed on the covariance matrix to obtain the left singular vector matrix and the right singular vector matrix; Calculate the rotation matrix using the left and right singular vector matrices; Calculate the translation vector using the reference centroid coordinates, the datum centroid coordinates, and the rotation matrix; A rigid transformation matrix is ​​constructed using the rotation matrix and translation vector.

7. The high-speed wire harness assembly method based on intelligent algorithm detection as described in claim 6, characterized in that, The process involves verifying the crimping quality of multiple crimped wires to obtain multiple qualified crimped wires, including: Perform the following operation on each of the multiple crimped wires: Obtain an image of the terminal area of ​​the crimped wire; The terminal area image is smoothed and filtered to obtain a noise-reduced image; Based on the pre-confirmed qualified terminal image, the noise-reduced image is used to locate the terminal to obtain the located image; Global illumination compensation is performed on the positioned image using the qualified terminal image to obtain the compensated image; Image difference processing is performed using the compensated image and the qualified terminal image to obtain the difference image; The difference image is binarized to obtain a binary difference image; The defect area is calculated using a binary difference image. The defect area is then compared with a preset defect area threshold. If the defect area is less than the defect area threshold, the crimped wire is considered a qualified crimped wire. By summarizing the qualified crimped wires, multiple qualified crimped wires are obtained.

8. The high-speed wire harness assembly method based on intelligent algorithm detection as described in claim 7, characterized in that, The step of performing global illumination compensation on the positioned image using the qualified terminal image to obtain the compensated image includes: The system acquires multiple actual grayscale values ​​of the image after positioning and multiple template grayscale values ​​of the qualified terminal image, wherein the actual grayscale values ​​correspond one-to-one with the template grayscale values. Calculate the mean and standard deviation of the actual grayscale using multiple actual grayscale values; Calculate the mean gray level and standard deviation of the template gray level using multiple template gray level values; For each of the multiple actual grayscale values, perform the following operation: The compensated gray value is calculated using the actual gray value, the actual gray mean, the actual gray standard deviation, the template gray mean, and the template gray standard deviation. The formula for calculating the compensated gray value is shown below: in, Indicates the compensation standard deviation, Indicates the standard deviation of template grayscale. Indicates the actual grayscale standard deviation. This represents the actual grayscale value. This represents the average grayscale value of the template. This represents the actual average gray level. By summing the aforementioned compensation grayscale values, multiple compensation grayscale values ​​are obtained; The multiple compensated grayscale values ​​are mapped to the localized image to obtain the compensated image.

9. A system using the high-speed wire harness assembly method based on intelligent algorithm detection as described in any one of claims 1 to 8, characterized in that, The system includes: The original wire stripping module is used to receive the wire harness assembly signal and determine the wire harness specifications based on the wire harness assembly signal; Multiple original conductors were identified based on the wire harness specifications; Perform the following operation on each of the multiple original conductors: The end face image of the original conductor is acquired to obtain the conductor image; The insulation layer thickness was determined based on the wire image; The original conductor is stripped using a laser wire stripper with pre-confirmed insulation layer thickness and a pre-determined insulation layer thickness to obtain a qualified stripped conductor. The core quality inspection module is used to inspect the cores of qualified stripped conductors and obtain a core inspection report, which indicates whether the conductor is qualified or unqualified. By summarizing the aforementioned core inspection reports, multiple core inspection reports are obtained; The wire terminal crimping module is used to identify multiple qualified wires based on multiple wire core test reports; Multiple qualified wires are used to crimp the terminals to obtain multiple crimped wires; The crimping quality of multiple crimped wires was checked, and multiple qualified crimped wires were obtained. The qualified wire bundling module is used to bundle multiple qualified crimped wires together to obtain multiple bundled wire bundles.

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